Have a personal or library account? Click to login
CHAID Decision Tree: Methodological Frame and Application Cover

CHAID Decision Tree: Methodological Frame and Application

Open Access
|Mar 2017

References

  1. Baran, B. & Kılıç, E. (2015). Applying the CHAID algorithm to analyze how achievement is influenced by university students’ demographics, study habits, and technology familiarity. Educational Technology & Society, 18 (2), 323-335.
  2. de Ville, B. (2006). Decision Trees for Business Intelligence and Data Mining: Using SAS Enterprise Miner. Cary, NC: SAS Institute Inc.
  3. Díaz-Pérez, M. F. & Bethencourt-Cejas, M. (2016). CHAID algorithm as an appropriate analytical method for tourism market segmentation. Journal of Destination Marketing & Management, 5 (3), 275-282, doi: 10.1016/j.jdmm.2016.01.006.
  4. Dulčić, Ž. & Vrdoljak-Raguž, I. (2007). Stilovi vođstva hotelskih menadžera Dubrovačkoneretvanske županije-empirijsko istraživanje. Ekonomski pregled, 58 (11), 709-731.
  5. Gonos, J. & Gallo, P. (2013). Model for leadership style evaluation. Management, 18(2), 157-168.
  6. Gorunescu, F. (2011). Data Mining: Concepts, Models and Techniques. Berlin: Springer.
  7. Hair, J.F.Jr., Black, W., Babin, B. & Anderson, R. (2010). Multivariate data analysis (8th ed). Upper Saddle River (New Jersey): Pearson Prentice Hall.
  8. Han, J., Kamber, M. & Pei, J. (2012). Data mining: concepts and techniques, (3rd ed). Amsterdam (etc.): Elsevier Inc.
  9. Horvat, I., Pejić Bach, M. & Merkač Skok, M. (2014), Decision tree approach to discovering fraud in leasing agreements. Business Systems Research, 5(2), 61-71, doi: 10.2478/bsrj-2014-0010.
  10. IBM (2012). IBM SPSS Decision Trees 21. Retrieved from: http://www.sussex.ac.uk/its/pdfs/SPSS_Decision_Trees_21.pdf Accessed on: September, 2016.
  11. Kağnicioğlu, H. C. & Moğol, M. (2014). Implementation of CHAID algorithm: a hotel case. International Journal of Research in Business and Social Science, 3(4), 42-52, doi: 10.20525/ijrbs.v3i4.116.
  12. Kantardzic, M. (2011). Data mining: concepts, models, methods, and algorithms (2nd ed). Hoboken, New Jersey: John Wiley & Sons.10.1002/9781118029145
  13. Kass, V. G. (1980). An Exploratory Technique for Investigating Large Quantities of Categorical Data. Journal of the Royal Statistical society, 29 (2), 119-127.10.2307/2986296
  14. Kim, S.S., Timothy, J. D. & Hwang, J. (2011). Understanding Japanese tourists’ shopping preferences using the Decision Tree Analysis method. Tourism Management, 32(3), 544-554, doi: 10.1016/j.tourman.2010.04.008.
  15. Maimon, O. & Rokach, L. (Eds.) (2010). Data mining and knowledge discovery handbook (2nd ed). New York: Springer.10.1007/978-0-387-09823-4
  16. Nisbet, R., Elder, J. & Miner, G. (2009). Handbook of statistical analysis and data mining applications. Amsterdam (etc.): Elsevier Inc.
  17. Northouse, P.G. (2012). Introduction to leadership: Concepts and Practice (2nd ed). Los Angeles (etc.): SAGE Publ.Inc.
  18. Novotná, M. (2012). The use of different approaches for credit rating prediction and their comparison. In: Proceedings of the 6th International Conference on Managing and Modelling of Financial Risks (pp. 448-457). [Availabe at SSRN: https://ssrn.com/abstract=2867. Accessed August, 23,2016.]
  19. Öcal, N., Ercan, K. M. & Kadıoğlu, E. (2015). Predicting financial failure using decision tree algorithms: an empirical test on the manufacturing industry at Borsa Istanbul. International Journal of Economics and Finance, 7(7), 189-206, doi:10.5539/ijef.v7n7p189.
  20. Republički zavod za statistiku (RZS), (2015). Preduzeća u Republici Srbiji prema veličini, u 2014. godini (Radni dokument, 90). Beograd: Republički zavod za statistiku.
  21. Petković, M., Janićijević N., Bogićević Milikić B. (2010). Organizacija (8th ed). Beograd: Ekonomski fakultet Univerziteta u Beogradu.
  22. Popescu, M. E., Andreica, M. & Micu, D. (2014). A method to improve economic performance evaluation using classification tree models. European Journal of Business and Social Sciences, 3 (4), 249-256.
  23. Rokach, L. & Maimon, O. (2008). Data mining with decision trees:theory and applications. New Jersey (etc.): World Scientific.
  24. Shmueli, G., Patel, N.R. & Bruce, P.C. (2010). Data mining for business intelligence concepts, techniques and applications in Microsoft Office Excel with Xlminer (2nd ed). Hoboken, New Jersey: John Wiley& Sons.
  25. Soldić-Aleksić, J. (2009). Prediktivni model segmentacije tržišta: primena modela logističke regresije i CHAID procedure. Marketing, 40 (3), 129-138.
  26. Stefanović, N. & Stefanović, Ž. (2007). Liderstvo i kvalitet. Kragujevac: Univerzitet u Kragujevcu, Mašinski fakultet.
  27. Stojanović-Aleksić, V. (2007). Liderstvo i organizacione promene. Kragujevac: Univerzitet u Kragujevcu, Ekonomski fakultet.
  28. Stojanović Aleksić, V., Stamenković, M. & Milanović, M. (2016). Analiza liderskih stilova u organizacijama u Srbiji: uticaj pola. Teme, XL(4), 1383-1397.
  29. Tufféry, S. (2011). Data mining and statistics for decision making. Chichester: John Wiley & Sons.10.1002/9780470979174
  30. Vercellis, C. (2009). Business intelligence: data mining and optimization for decision making. Chichester: John Wiley & Sons.10.1002/9780470753866
  31. Witten, H. I. & Frank E. (2005). Data mining: practical machine learning tools and techniques (2nd ed). Amsterdam (etc.): Elsevier Inc.
DOI: https://doi.org/10.1515/ethemes-2016-0029 | Journal eISSN: 2217-3668 | Journal ISSN: 0353-8648
Language: English
Page range: 563 - 586
Submitted on: Dec 12, 2016
Accepted on: Feb 1, 2017
Published on: Mar 16, 2017
Published by: University of Niš, Faculty of Economics
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2017 Marina Milanović, Milan Stamenković, published by University of Niš, Faculty of Economics
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.